Pretreatment Magnetic Resonance Imaging Research Articles

MRI-based Nomogram Predicts the Risk of Progression of Unresectable Hepatocellular Carcinoma After Combined Lenvatinib and anti-PD-1 Antibody Therapy

Combined immune and anti-angiogenic treatment has shown promising results for unresectable hepatocellular carcinoma (HCC), but with a high risk of early progression. In this study, we aimed to investigate whether pre-treatment magnetic resonance imaging (MRI) features and MRI-based nomogram could predict the risk of disease progression of unresectable HCC after first-line lenvatinib/anti-PD-1 antibody therapy. Thirty-seven HCC participants with qualified pre-treatment contrast-enhanced MRI were enrolled. All patients received combined lenvatinib and anti-PD-1 antibody treatment. Progression free survival rate was analyzed using the Kaplan-Meier method. Potential clinical-radiological risk factors for progression were analyzed using the log-rank tests and Cox regression model. The performance of MRI-based nomogram was evaluated based on C-index, calibration, and decision curve analyses. The 6-month and 12-month cumulative progression free survival rates were 59.5% (95% confidence interval (CI), 43.6%-75.4%) and 48.0% (95% CI, 31.7%-64.3%). On multivariate analysis, no or incomplete tumor capsule (hazard ratio (HR)=15.215 [95% CI 2.707-85.529], p=0.002), heterogeneous signal on T2-weighted imaging (HR=28.179 [95% CI 2.437-325.838]; p=0.008) and arterial contrast-to-noise ratio ≤95.45 (HR=5.113 [95% CI 1.538-17.00]; p=0.008) were independent risk factors for disease progression. Satisfactory predictive performance of the nomogram incorporating the three independent imaging features was obtained with a C-index value of 0.880 (95% CI 0.824-0.937), and the combined nomogram had more favorable clinical prediction performance than any single feature. MRI features can be considered effective predictors of disease progression for unresectable HCC with first-line lenvatinib plus anti-PD-1 antibody therapy, and the combined MRI-based nomogram achieved a superior prognostic model, which may help to identify appropriate candidates for the therapy.

Radiologic criteria of retropharyngeal lymph node metastasis in maxillary sinus cancer

ObjectiveTo determine the most appropriate radiologic criteria of metastatic retropharyngeal lymph nodes (RLNs) in patients with maxillary sinus cancer (MSC).Materials and methodsWe retrospectively evaluated 16 consecutive patients who underwent magnetic resonance imaging (MRI) before and after the treatment of locally advanced squamous cell carcinoma of the maxillary sinus. The minimal and maximal diameters of all RLNS were recorded. RLNs were classified as metastatic on the basis of the MRI follow-up (f/u). RLNs were considered non-metastatic if stable disease continued until the final MRI f/u and metastatic in cases with different evaluations (complete response, partial response, progressive disease) determined using Response Evaluation Criteria in Solid Tumours (RECIST) ver. 1.1. The receiver operating characteristic curve (ROC) and area under the curve (AUC) were used to assess the accuracy of various criteria in the diagnosis of metastatic RLNs.ResultsOf the 34 RLNs in 16 cases observed on pretreatment MRI, 7 were classified as metastatic RLNs and 27 as non-metastatic RLNs. Using the radiologic criteria, metastatic RLNs tended to be diagnosed more accurately with the minimal axial diameter than with the maximal axial diameter (AUC; 0.97 vs. 0.73, p = 0.06). The most accurate size criterion of metastatic RLNs was a minimal axial diameter of 5 mm or larger, with an accuracy of 94.1% (32 of 34).ConclusionsThe most appropriate radiologic criterion of metastatic RLNs in MSC is a minimal axial diameter of 5 mm or longer.

Radiomic Features of T2-weighted Imaging and Diffusion Kurtosis Imaging in Differentiating Clinicopathological Characteristics of Cervical Carcinoma

Clinicopathological characteristics including histological subtypes, tumour grades and International Federation of Gynecology and Obstetrics (FIGO) stages are crucial factors in the clinical decision for cervical carcinoma (CC). The purpose of this study was to evaluate the ability of T2-weighted imaging (T2WI) and diffusion kurtosis imaging (DKI) radiomics in differentiating clinicopathological characteristics of CC. One hundred and seventeen histologically confirmed CC patients (mean age 56.5 ± 14.0 years) with pre-treatment magnetic resonance imaging were retrospectively reviewed. DKI was acquired with 4 b-values (0-1500 s/mm2). Volumes of interest were contoured around the tumours on T2WI and DKI. Radiomic features including shape, first-order and grey-level co-occurrence matrix with wavelet transforms were extracted. Intraclass correlation coeffient between 2 radiologists was used for features reduction. Feature selection was achieved by elastic net and minimum redundancy maximum relevance. Selected features were used to build random forest (RF) models. The performances for differentiating histological subtypes, tumour grades and FIGO stages were assessed by receiver operating characteristic analysis. Area under the curves (AUCs) for T2WI-only RF models for discriminating histological subtypes, tumour grades and FIGO stages were 0.762, 0.686, and 0.719. AUCs for DWI-only models were 0.663, 0.645, and 0.868, respectively. AUCs of the combined T2WI and DKI models were 0.823, 0.790, and 0.850, respectively. T2WI and DKI radiomic features could differentiate the clinicopathological characteristics of CC. A combined model showed excellent diagnostic discrimination for histological subtypes, while a DKI-only model presented the best performance in differentiating FIGO stages.

Different Primary Sites of Hypopharyngeal Cancer Have Different Lymph Node Metastasis Patterns: A Retrospective Analysis From Multi-Center Data.

BackgroundMost hypopharyngeal cancers (HPCs) develop lymph node metastasis (LNM) at initial diagnosis. Understanding the pattern of LNM in HPC could help both surgeons and radiologists make decisions in the management of cervical lymph nodes.MethodsA total of 244 newly diagnosed HPC patients between January 2010 and December 2018 were recruited from three specialized cancer hospitals in mainland China. All patients received pre-treatment magnetic resonance imaging (MRI), and definitive radiotherapy with or without concurrent chemotherapy. We reassessed the features of the primary tumor (tumor size, primary location, and extent of invasion) and the involvement of lymph nodes at each level. According to the incidence of LNM, these levels were sequenced and sorted into drainage stations. Univariate and multivariate analyses were used to determine the risk factors for bilateral and regional lymph node metastasis.ResultsThe cohort consisted of 195 piriform sinus cancers (PSC), 47 posterior wall cancers (PWC), and 2 post-cricoid cancers (PCC). A total of 176 patients (72.1%) presented with MRI-detectable LNMs. The overall LNM rates for level II-VI and retropharyngeal lymph nodes (RPLNs) were 59.0%, 52.9%, 14.3%, 1.6%, 2.9%, and 16.4%, respectively. Based on the prevalence of LNM at each level, we hypothesize that the lymphatic drainage of PSC was carried out in sequence along three stations: Level II and III (61.0% and 55.4%), Level IV and RPLN (15.9% and 11.3%), and Level V and VI (1.5% and 3.1%). For PWCs, lymphatic drainage is carried out at two stations: Level II, III, and RPLN (48.9%, 40.4%, and 34.0%) and Level IV-VI (6.4%, 0%, and 2.1%). According to univariate and multivariate analyses, posterior wall invasion was significantly correlated with bilateral LNM (P = 0.030, HR = 2.853 95%CI, 1.110-7.338) and RPLN metastasis (P = 0.017, HR = 2.880 95%CI, 1.209-6.862). However, pyriform sinus invasion was less likely to present with bilateral LNM (P = 0.027, HR = 0.311, 95%CI, 0.111-0.875) and RPLN metastasis (P = 0.028, HR = 0.346, 95%CI, 0.134-0.891).Conclusions and RelevanceThe primary tumor site and extent of invasion are related to the pattern of lymph node metastasis. That is, the metastasis would drainage station by station along different directions.

Radiomics Analysis of Fat-Saturated T2-Weighted MRI Sequences for the Prediction of Prognosis in Soft Tissue Sarcoma of the Extremities and Trunk Treated With Neoadjuvant Radiotherapy.

PurposeTo create a prognostic prediction radiomics model for soft tissue sarcoma (STS) of the extremities and trunk treated with neoadjuvant radiotherapy.MethodsThis study included 62 patients with STS of the extremities and trunk who underwent magnetic resonance imaging (MRI) before neoadjuvant radiotherapy. After tumour segmentation and preprocessing, 851 radiomics features were extracted. The radiomics score was constructed according to the least absolute shrinkage and selection operator (LASSO) method. Survival analysis (disease-free survival; DFS) was performed using the log-rank test and Cox’s proportional hazards regression model. The nomogram model was established based on the log-rank test and Cox regression model. Harrell’s concordance index (C-index), calibration curve and receiver operating characteristic (ROC) curve analysis were used to evaluate the prognostic factors. The clinical utility of the model was assessed by decision curve analysis (DCA).ResultsThe univariate survival analysis showed that tumour location (p = 0.032), clinical stage (p = 0.022), tumour size (p = 0.005) and the radiomics score were correlated with DFS (p < 0.05). The multivariate analysis showed that tumour location, tumour size, and the radiomics score were independent prognostic factors for DFS (p < 0.05). The combined clinical-radiomics model based on the multivariate analysis showed the best predictive ability for DFS (C-index: 0.781; Area Under Curve: 0.791). DCA revealed that the use of the radiomics score-based nomogram was associated with better benefit gains relative to the prediction of 2-year DFS events than other models in the threshold probability range between 0.12 and 0.38.ConclusionThe radiomics score from pretreatment MRI is an independent prognostic factor for DFS in patients with STS of the extremities and trunk. The radiomics score-based nomogram could improve prognostic stratification ability and thus contribute to individualized therapy for STS patients.

Features from MRI texture analysis associated with survival outcomes in triple-negative breast cancer patients

The purpose of the study is to evaluate the associations between intratumoral or peritumoral textural features derived from pretreatment magnetic resonance imaging (MRI) and recurrence-free survival (RFS) in triple-negative breast cancer (TNBC) patients. Forty-three patients with TNBC who underwent preoperative MRI between February 2008 and March 2014 were included. We performed two-dimensional texture analysis on the intratumoral or peritumoral region of interest (ROI) on axial of T2-weighted image (T2WI), dynamic contrast-enhanced (DCE)-MRI and DCE-MRI subtraction images. We also analyzed histopathological data. Cox proportional hazards models were used to investigate associations with survival outcomes. Twelve of the 43 patients (27.9%) had recurrence disease, at a median of 32.5months follow-up (1.4-61.5months). In univariate analysis, nine texture features in T2WI and DCE-MRI subtraction images were significantly associated with RFS. In multivariate analysis, intratumoral difference entropy in DCE-MRI subtraction images in the initial phase (hazard ratio 11.71; 95% confidence interval (CI) [1.41, 97.00]; p value 0.023) and, peritumoral difference variance in DCE-MRI subtraction images in the delayed phase (hazard ratio 9.60; 95% CI [1.98, 46.51]; p value 0.005), were both independently associated with RFS. Moreover, multivariate analysis revealed the presence of lymphovascular invasion as independently associated with RFS (hazard ratio 8.13; 95% CI [2.16, 30.30]; p value 0.002). At pretreatment MRI, an intratumoral and peritumoral quantitative approach using texture analysis has the potential to serve as a prognostic marker in patients with TNBC.

Magnetic resonance imaging radiomics signatures for predicting endocrine resistance in hormone receptor-positive non-metastatic breast cancer

BackgroundOne-third of patients with hormone receptor (HR)-positive breast cancers fail to respond to hormone therapy, and some patients even progress within two years of adjuvant endocrine therapy (ET) toward primary endocrine resistance. However, there is no effective way to predict endocrine resistance. ObjectiveTo build a model that incorporates the radiomic signature of pretreatment magnetic resonance imaging (MRI) with clinical information to predict endocrine resistance. MethodsClinical data of non-metastatic breast cancer patients diagnosed between May 1, 2015 and December 31, 2018 and preoperative dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) were retrospectively collected from three hospitals in China. The significant clinicopathological characteristics and radiomic signatures were included in multivariable logistic regression to establish a combined model to predict endocrine resistance in the training set, and validate the internal and external validation set. ResultsA total of 744 female non-metastatic breast cancer patients from three hospitals in China were included. In the training cohort, the AUC of the Radiomic-Clinical combined model to predict endocrine resistance was 0.975, which was higher than clinical model (0.849), IHC4 model (0.682) and similar as radiomic model (0.941). Also, the AUC of the combined model in the internal (0.921) and external validation cohort (0.955) were higher than clinical model and IHC4 model. The sensitivity of combined model was higher than radiomic alone, and got the best thresholding of the AUC. ConclusionThis study developed and validated a pretreatment multiparametric MRI-based radiomic-clinical combined model and showed good performance in predicting endocrine resistance.

Malignant Features in Pretreatment Metastatic Lateral Lymph Nodes in Locally Advanced Low Rectal Cancer Predict Distant Metastases.

Pretreatment enlarged lateral lymph nodes (LLN) in patients with locally advanced low rectal cancer are predictive for local recurrences after neoadjuvant (chemo)radiotherapy (n(C)RT) followed by total mesorectal excision (TME). Not much is known of the impact on oncological outcomes when in addition malignant features are present in enlarged LLN. A multicenter retrospective cohort study was conducted at five tertiary referral centers in the Netherlands and Australia. All patients were diagnosed with locally advanced low rectal cancer with LLN on pretreatment magnetic resonance imaging (MRI) and underwent n(C)RT followed by TME. LLN were considered enlarged with a short axis of ≥5mm. Malignant features were defined as nodes with internal heterogeneity and/or border irregularity. Outcomes of interest were local recurrence-free survival (LRFS), distant metastatic-free survival (DMFS), and overall survival (OS). Out of 115 patients, the majority was male (75%) and the median age was 64 years (range 26-85years). Median pretreatment LLN short axis was 7mm (range 5-28mm), and 60 patients (52%) had malignant features. After a median follow-up of 47months, patients with larger LLN (7+mm) had a worse LRFS (p=0.01) but no difference in DMFS (p=0.37) and OS (p=0.54) compared with patients with smaller LLN (5-6mm). LLN patients with malignant features had no difference in LRFS (p=0.20) but worse DMFS (p=0.004) and OS (p=0.006) compared with patients without malignant features in the LLN. Cox regression analysis identified LLN short axis as an independent factor for LR. Malignant features in LLN were an independent factor for DMFS. The current study suggests that pretreatment enlarged LLN that also harbor malignant features are predictive of a worse DMFS. More studies will be required to further explore the role of malignant features in LLN.

MRI-based three-dimensional reconstruction for staging cervical cancer and predicting high-risk patients.

BackgroundCervical tumors usually have an irregular morphology. It is often difficult to estimate tumor size or volume based on a diameter measurement from a two-dimensional magnetic resonance imaging slice. This study aimed to explore the use of magnetic resonance imaging-based three-dimensional reconstruction in cervical cancer.MethodsWe retrospectively created a three-dimensional reconstruction based on the pre-treatment magnetic resonance imaging data of 54 cervical cancer patients at a single center to evaluate tumor size and extent of invasion, as well as to review cervical cancer staging and treatment. The tissues and organs were automatically outlined by the three-dimensional application, based on the signal intensity difference of magnetic resonance imaging data.ResultsThe maximum tumor diameters calculated using the magnetic resonance imaging-based three-dimensional reconstruction were larger than those calculated from the direct magnetic resonance imaging findings or gynecological examinations. Initial underestimation of the maximum tumor diameter led to under-staging in up to 29.6% of patients. The magnetic resonance imaging-based three-dimensional reconstruction revealed that upstaging was warranted based on lymph node metastasis (3.7% of patients) and invasion of the vaginal fornix (1.9% of patients). Lymph node metastasis was associated with a significantly larger tumor volume (P<0.05). A volume cut-off value ≥18.6 mL provided 60% sensitivity, 96.7% specificity, 75% positive predictive value and 93.5% negative predictive value for predicting high-risk patients (P<0.05).ConclusionsMagnetic resonance imaging-based three-dimensional reconstruction is a new approach that could potentially measure cervical cancer more accurately.

Percutaneous Radiofrequency Rhizotomy Is Equally Effective for Trigeminal Neuralgia Patients with or Without Neurovascular Compression.

Neurovascular compression (NVC) in patients with trigeminal neuralgia (TN) can be a factor of treatment outcome, especially in microvascular decompression and stereotactic radiosurgery. No such effect has been reported in percutaneous radiofrequency rhizotomy (RF). This study aims to investigate whether NVC affects the efficacy of RF in patients with TN. We retrospectively reviewed patients with TN who received RF in our institution. Pretreatment magnetic resonance imaging was performed in every patient, and the presence of NVC was reviewed independently by two physicians. The patients were followed up at least for a year after the treatment. Pain severity was assessed with a numeric rating scale (NRS). Sixty-two patients were included in the study. All of the patients had single-sided lesions, and 35 patients had NVC. There were no significant differences between these two groups of patients in terms of gender distribution, age, and pretreatment pain severity. Comparable pain severity improvement was found at 1-year follow-up between these two groups (NRS 7.93 ± 0.492 without compression vs 7.57 ± 0.451 with compression, P = 0.600). No significant difference in posttreatment pain severity at 1 year was found between these two patient groups (NRS 1.37 ± 0.466 without compression vs 1.66 ± 0.458 with compression, P = 0.667). For patients with TN treated by RF, the presence or absence of NVC is not likely to affect the 1-year pain control rate.

Predicting the pathological grade of breast phyllodes tumors: a nomogram based on clinical and magnetic resonance imaging features.

To explore the potential factors related to the pathological grade of breast phyllodes tumors (PTs) and to establish a nomogram to improve their differentiation ability. Patients with PTs diagnosed by post-operative pathology who underwent pretreatment magnetic resonance imaging (MRI) from January 2015 to June 2020 were retrospectively reviewed. Traditional clinical features and MRI features evaluated according to the fifth BI-RADS were analyzed by statistical methods and introduced to a stepwise multivariate logistic regression analysis to develop a prediction model. Then, a nomogram was developed to graphically predict the probability of non-benign (borderline/malignant) PTs. Finally, 61 benign, 73 borderline and 48 malignant PTs were identified in 182 patients. Family history of tumor, diameter, lobulation, cystic component, signal on fat saturated T2 weighted imaging (FS T2WI), BI-RADS category and time-signal intensity curve (TIC) patterns were found to be significantly different between benign and non-benign PTs. The nomogram was finally developed based on five risk factors: family history of tumor, lobulation, cystic component, signal on FS T2WI and internal enhancement. The AUC of the nomogram was 0.795 (95% CI: 0.639, 0.835). Family history of tumor, lobulation, cystic components, signals on FS T2WI and internal enhancement are independent predictors of non-benign PTs. The prediction nomogram developed based on these features can be used as a supplemental tool to pre-operatively differentiate PTs grades. More sample size and characteristics were used to explore the factors related to the pathological grade of PTs and establish a predictive nomogram for the first time.

Pre-Clinical Study of Ibrutinib for the Treatment of T-Cell Lymphoma Using Magnetic Resonance Imaging (MRI) Assessment

Peripheral T cell lymphoma (PTCL) has a poor prognosis and there is a need for new treatments.The sanroque mouse bears a mutation in the E3 ubiquitin ligase, Roquin, which leads to T-cell activation and autoimmunity in homozygous animals. In heterozygous mice (Roquinsan/+) T-cell lymphomas with histological similarity to human angioimmunoblastic lymphoma (AITL), the commonest subtype of PTCL, develop in 40 to 50% of animals by 6 - 12 months of age.In order to test the feasibility of using sanroque mice for pre-clinical work we carried out MRI scans of the axillary and inguinal regions before and after receiving 200mg/kg cyclophosphamide as an intra-peritoneal injection. After 28-days the MRI scans were repeated and lymph nodes, spleens and livers collected.MRI scanning was performed on a 9.4T Agilent scanner (Agilent Technologies, Santa Claire, CA, USA) with a 310mm bore diameter and 6cm inner-diameter gradient (1000mT/m maximum gradient strength). A 4cm millipede RF coil was used for RF transmission and reception. T2-weighted images were acquired using a respiratory-gated fast spin echo (FSE) sequence with TR/TE=3000/40ms, 40x40mm field of view (256x256 matrix), 32x0.8mm slices and two signal averages.Enlarged lymph nodes were identified on the pre-treatment MRI scan and compared to the equivalent lymph node following treatment (Figure 1A). There was a mean 94% reduction in lymph node size following cyclophosphamide treatment. This demonstrated that the enlarged lymph nodes were chemosensitive and that MRI scanning could be used to monitor the lymph node size in response to treatment.Interleukin-2-inducible kinase (ITK) is expressed and has essential functions in regulating normal T-cell proliferation and differentiation. ITK is also expressed in AITL and might be a therapeutic target but there is no pre-clinical data. The small molecule BTK/ITK inhibitor, ibrutinib, is effective and well tolerated in clinical practice in some B-cell lymphomas and ibrutinib is active against mouse ITK.In order to assess the effect of ibrutinib on (Roquinsan/+) T-cell lymphoma we identified twelve mice with palpable lymph nodes. Following an MRI scan, oral treatment with ibrutinib (25mg/kg in 1% (2-Hydroxypropyl)-β-cyclodextrin (2HPBD)) or equivalent volume of vehicle (1% 2HPBD) was given daily by gavage. Five mice were treated with ibrutinib for 28 days and three for reduced time periods (7 days, 14 days and 21 days). Four mice were treated with vehicle for 28 days. Following cessation of therapy a further MRI scan was performed prior to harvesting of tissues, including liver, spleen and lymph nodes. MRI images were analysed to determine the change in volume of lymph nodes during the treatment period.Responses to ibrutinib were mixed (Figure 1B & 1C): of those that received 28 days treatment 5/8 animals showed reduction in tumour size of between 10 and 86% whilst those that received shorter durations of treatment showed reductions of 8 and 11%. 3/8 ibrutinib treated animals showed increases in tumour size of 9 and 85% (mice treated for 28 days) whilst one animal treated for 7 days showed an increase of 117%. 3/4 vehicle treated animals showed stable or increasing lymphadenopathy whilst one mouse showed spontaneous tumour regression.In order to analyze the effects of ibrutinib at the cellular level we established flow cytometry protocols to determine cellular composition. Previous reports show that the majority of cells within sanroque enlarged lymph nodes are B-cells with a minority (1 to 2%) being malignant T-cells. This is similar to the pattern observed in human Tfh lymphoma. Lymph nodes were harvested following the post-treatment MRI scan and cell suspensions produced. The proportions of CD4+, CD8+ and B220+ lymphocytes were assessed. To determine the Tfh cell population CD4 positive lymphocytes were gated and the proportion of CXCR5hiPD1hi cells assessed. We did not observe any significant differences between responding and non-responding mice (Figure 1D) or treated and untreated mice.We have developed an MRI protocol to assess the response of a T-cell lymphoma model to novel agents to facilitate pre-clinical studies. We interpret our results as showing that ibrutinib is effective as a single agent in a proportion of the spontaneous T-cell lymphomas generated in the Roquinsan/+ model of Tfh lymphoma but further work is required to understand the differences between responder and non-responder tumours. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.

Patterns of failure and implications for clinical target volume definition of locally advanced T4b rectal cancer identified with magnetic resonance imaging and treated using neoadjuvant chemoradiotherapy and surgery

Background and purposeElective irradiation of the external iliac lymph nodes (EIN) has always been advocated for T4b rectal cancer with anterior organ invasion without convincing evidence. This study aimed to explore the patterns of treatment failure for locally advanced T4b rectal cancer treated using neoadjuvant chemoradiotherapy (NCRT) and surgery. This information may help to clarify whether the current definition of the clinical target volume (CTV) is still appropriate. Materials and methodsWe retrospectively analyzed data from 126 patients with locally advanced T4b rectal cancer who received NCRT, without elective EIN irradiation, followed by surgery between January 2010 and October 2018. Pretreatment magnetic resonance imaging was used to identify the T4b disease in all cases. The locoregional recurrence (LRR) rate and EIN failure rate were evaluated, and the LRR locations were identified using a three-dimensional model. ResultsAfter a median follow-up of 53.9 months, LRR occurred in 11.1% of patients (14/126). All LRRs were located in the previously irradiated fields and below the S2–S3 junction. The EIN failure rate was 0.8% (1/126) among all patients and 1.8% (1/56) in the group with anterior genitourinary organ invasion. The estimated 4-year distant relapse-free survival, disease-free survival and overall survival were 79.3%, 73.2% and 86.9%, respectively. ConclusionsIt may be feasible to exclude the external iliac region from the CTV during NCRT for locally advanced T4b rectal cancer. However, further studies are needed to clarify whether the cranial border of the CTV can be lowered.

Retropharyngeal Lymph Node Metastasis Diagnosed by Magnetic Resonance Imaging in Hypopharyngeal Carcinoma: A Retrospective Analysis From Chinese Multi-Center Data.

BackgroundTo assess the prevalence, risk factors and prognostic significance of retropharyngeal lymph node (RPLN) metastasis diagnosed by magnetic resonance imaging (MRI) in patients with hypopharyngeal squamous cell carcinoma (HPSCC).Methods259 patients from three cancer institutions in China from Jan 2010 to Dec 2018 were analyzed, retrospectively. All the patients had been given pre-treatment magnetic resonance imaging (MRI) of head and neck and were then treated with definitive radiotherapy with or without chemotherapy. Pretreatment diagnostic MRIs were reviewed by a dedicated head and neck radiologist, for the presence or absence of radiographically positive RPLN, cervical LN and tumor invasion.Demographic variables were analysed by descriptive statistics using SPSS 20.0. Predictors of the presence of RPLN and its prognostic significance were examined.ResultsRPLN metastasis was discovered in 44 patients (17%). Logistic analysis showed that posterior pharyngeal wall (PPW) primary tumor; PPW invasion; N2-3; multiple cervical lymph node (LN) involvement (>2 LNs) were associated with RPLN metastasis, with metastasis rates 37%, 30%, 31% and 33% respectively. Patients with RPLN metastasis had a significantly reduced 5-year overall survival (OS) and disease-free survival (DFS) compared to the non-RPLN metastasis group (OS 28% vs. 48%, p=0.001; DFS 25% vs. 41%, p=0.040).ConclusionsRPLN metastasis was not uncommon in HPSCC patients. Risk factors were: PPW primary tumor, PPW invasion and cervical LN status. RPLN metastasis is a poor prognosticator for survival.

Prognostic role of pre-treatment magnetic resonance imaging (MRI)-based radiomic analysis in effectively cured head and neck squamous cell carcinoma (HNSCC) patients

Objectives To identify and validate baseline magnetic resonance imaging (b-MRI) radiomic features (RFs) as predictors of disease outcomes in effectively cured head and neck squamous cell carcinoma (HNSCC) patients. Materials and methods Training set (TS) and validation set (VS) were retrieved from preexisting datasets (HETeCo and BD2Decide trials, respectively). Only patients with both pre- and post-contrast enhancement T1 and T2-weighted b-MRI and at least 2 years of follow-up (FUP) were selected. The combination of the best extracted RFs was used to classify low risk (LR) vs. high risk (HR) of disease recurrence. Sensitivity, specificity, and area under the curve (AUC) of the radiomic model were computed on both TS and VS. Overall survival (OS) and 5-year disease-free survival (DFS) Kaplan–Meier (KM) curves were compared for LR vs. HR. The radiomic-based risk class was used in a multivariate Cox model, including well-established clinical prognostic factors (TNM, sub-site, human papillomavirus [HPV]). Results In total, 57 patients of TS and 137 of VS were included. Three RFs were selected for the signature. Sensitivity of recurrence risk classifier was 0.82 and 0.77, specificity 0.78 and 0.81, AUC 0.83 and 0.78 for TS and VS, respectively. VS KM curves for LR vs. HR groups significantly differed both for 5-year DFS (p<.0001) and OS (p=.0004). A combined model of RFs plus TNM improved prognostic performance as compared to TNM alone, both for VS 5-year DFS (C-index: 0.76 vs. 0.60) and OS (C-index: 0.74 vs. 0.64). Conclusions Radiomics of b-MRI can help to predict recurrence and survival outcomes in HNSCC.

MRI-based radiomics signature for the prediction of response of lung cancer brain metastases after whole-brain radiotherapy.

e21096 MRI-based Radiomics signature for the Prediction of Response of Lung Cancer Brain Metastases After Whole-Brain Radiotherapy Background: Local response prediction for brain metastases (BMs) from lung cancer after Whole-Brain Radiotherapy (WBRT) is challenging, as existing criteria are based solely on unidimensional measurements. This study sought to determine whether radiomic features of lung cancer BMs derived from pre-treatment magnetic resonance imaging (MRI) could be used to predict local response following WBRT. Methods: A total of 88 Lung Cancer patients with BMs treated with WBRT were analyzed. After volumes of interest were drawn, 944 radiomic features including first-order, shape, Gray Level Co-occurrence Matrix (GLCM), Gray Level Dependence Matrix (GLDM), Gray Level Run Length Matrix (GLRLM), Gray Level Size Zone Matrix (GLSZM), Neighborhood Gray Tone Difference Matrix (NGTDM), and Laplacian of Gaussian (LoG) features were extracted, using the baseline pre-treatment post-contrast T1 (T1c) and T2 fluid-attenuated inversion recovery (FLAIR) MRI sequences, respectively. Local response status was determined by contrasting the baseline and follow-up MRI according to the RANO-BM criteria. The independent samples t test or Mann-Whitney U test, and then least absolute shrinkage and selection operator (LASSO) were used for dimensionality reduction and feature selection. An adaboost classifier was trained using the selected radiomic features and evaluated using the area under the receiver operating characteristic curve (AUC) in both the training and testing sets. Other discrimination metrics, including classification accuracy, positive predictive value (PPV), negative predictive value (NPV), sensitivity, and specificity, were also calculated. Results: The optimal radiomics signature was developed based on a multivariable logistic regression with 4, 5, 6 radiomic features on T1c, T2 FLAIR and T1c+T2 FLAIR, respectively. The radiomics model based on T1c features presented the AUC of (0.920 vs. 0.805, respectively) for both the training and testing sets, followed by T2 FLAIR features (0.893 vs. 0.701, respectively), and T1c+T2 FLAIR features (0.971 vs. 0.857, respectively). The classification accuracy of the radiomics model also well predicted the local response of BMs for both the the training and testing sets (T1c: 82.9% vs. 77.8%, T2 FLAIR: 82.9% vs. 77.8%, T1c+T2 FLAIR: 90.0% vs. 77.8%, respectively). Conclusions: Radiomics holds promise for predicting local tumor response following WBRT in patients with lung cancer and brain metastases. A predictive model built on radiomic features from an institutional cohort performed well on cross-validation testing. These results warrant further validation in independent datasets. Such work could prove invaluable for guiding management of individual patients and assessing outcomes of novel interventions.

MRI in head and neck cancer following chemoradiotherapy: what is the optimal delay to demonstrate maximal response?

ObjectivesTo investigate the optimal timing for post-chemoradiotherapy (CRT) reference magnetic resonance imaging (MRI) in head and neck cancer, so as to demonstrate a maximal treatment response. To assess whether this differs in human papillomavirus–related oropharyngeal cancer (HPV-OPC) and whether the MRI timing impacts on the ability to predict treatment success.MethodsFollowing ethical approval and informed consent, 45 patients (40 male, mean age 59.7 ± 7.9 years, 33 HPV-OPC) with stage 3 and 4 HNSCC underwent pre-treatment, 6- and 12-week post-CRT MRIs in this prospective cohort study. Primary tumour (n = 39) size, T2w morphology and diffusion weight imaging (DWI) scores, together with nodal (n = 42) size and necrotic/cystic change, were recorded. Interval imaging changes were analysed for all patients and according to HPV-OPC status. MRI descriptors and their interval changes were also compared with 2-year progression-free survival (PFS).ResultsAll MRI descriptors significantly changed between pre-treatment and 6-week post-treatment MRI studies (p < .001). Primary tumour and nodal volume decreased between 6- and 12-week studies; however, interval changes in linear dimensions were only evident for HPV-OPC lymph nodes. Nodal necrosis scores also evolved after 6 weeks but other descriptors were stable. The 6-week nodal necrosis score and the 6- and 12-week nodal volume were predictive of 2-year PFS.ConclusionApart from HPV-OPC patients with nodal disease, the 6-week post-CRT MRI demonstrates maximal reduction in the linear dimensions of head and neck cancer; however, a later reference study should be considered if volumetric analysis is applied.Key Points• This study provides guidance on when early post-treatment imaging should be performed in head and neck cancer following chemoradiotherapy, in order to aid subsequent detection of recurrent tumour.• Lymph nodes in HPV-related oropharyngeal cancer patients clearly reduced in size from 6 to 12 weeks post-treatment. However, other lymph node disease and all primary tumours showed only a minor reduction in size beyond 6 weeks, and this required a detailed volumetric analysis for demonstration.• Timing of the reference MRI following chemoradiotherapy for head and neck cancer depends on whether the patient has HPV-related oropharyngeal cancer and whether there is nodal disease. MRI as early as 6 weeks post-treatment may be performed unless volumetric analysis is routinely performed.

MRI-Based Radiomics Analysis for the Pretreatment Prediction of Pathologic Complete Tumor Response to Neoadjuvant Systemic Therapy in Breast Cancer Patients: A Multicenter Study.

Simple SummaryThe prediction of pathologic complete response (pCR) to neo-adjuvant systemic therapy (NST) based on radiological assessment of pretreatment MRI exams in breast cancer patients is not possible to date. In this study, we investigated the value of pretreatment MRI-based radiomics analysis for the prediction of pCR to NST. Radiomics, clinical, and combined models were developed and validated based on MRI exams containing 320 tumors collected from two hospitals. The clinical models significantly outperformed the radiomics models for the prediction of pCR to NST and were of similar or better performance than the combined models. This indicates poor performance of the radiomics features and that in these scenarios the radiomic features did not have an added value for the clinical models developed. Due to previous and current work, we tentatively attribute the lack of significant improvement in clinical models following the addition of radiomics features to the effects of variations in acquisition and reconstruction parameters. The lack of reproducibility data meant this effect could not be analyzed. These results indicate the need for reproducibility studies to preselect reproducible features in order to properly assess the potential of radiomics.This retrospective study investigated the value of pretreatment contrast-enhanced Magnetic Resonance Imaging (MRI)-based radiomics for the prediction of pathologic complete tumor response to neoadjuvant systemic therapy in breast cancer patients. A total of 292 breast cancer patients, with 320 tumors, who were treated with neo-adjuvant systemic therapy and underwent a pretreatment MRI exam were enrolled. As the data were collected in two different hospitals with five different MRI scanners and varying acquisition protocols, three different strategies to split training and validation datasets were used. Radiomics, clinical, and combined models were developed using random forest classifiers in each strategy. The analysis of radiomics features had no added value in predicting pathologic complete tumor response to neoadjuvant systemic therapy in breast cancer patients compared with the clinical models, nor did the combined models perform significantly better than the clinical models. Further, the radiomics features selected for the models and their performance differed with and within the different strategies. Due to previous and current work, we tentatively attribute the lack of improvement in clinical models following the addition of radiomics to the effects of variations in acquisition and reconstruction parameters. The lack of reproducibility data (i.e., test-retest or similar) meant that this effect could not be analyzed. These results indicate the need for reproducibility studies to preselect reproducible features in order to properly assess the potential of radiomics.

Canine presumed glial brain tumours treated with radiotherapy: Is there an inferior outcome in tumours contacting the subventricular zone?

Post-treatment outcome in canine glial tumours is described with a broad range of survival times between 2 and 28 months. After surgery or radiation therapy, the tumours may progress locally or spread within the central nervous system. It is unknown if tumour- or patient-specific factors influence prognosis. In humans, glioblastoma involving the subventricular zone has been found to recur distantly, with shortened time to progression and overall survival. We included 32 dogs irradiated for a presumptive primary glial brain tumour in this retrospective cohort study. Tumours were grouped relative to subventricular zone contact and overt ventricular invasion assessing pre-treatment magnetic resonance images. Median time to progression (TTP) for all cases was 534 days (95%CI, 310-758), with a significantly shorter TTP in dogs with lesions at the subventricular zone (median TTP, 260 vs. 687 days; p=.049). Tumours at the subventricular zone progressed more often (p=.001), and more likely as CNS-metastasis (52.9% vs. 13.3%, p=.028). Median overall survival (OS) was 489 days (95%CI, 147-831) and median tumour-specific survival 609 days (95%CI, 382-835). Involvement of the subventricular zone was significantly associated with a shorter tumour-specific survival (median, 306 vs. 719 days; p=.044). Glial tumours contacting the subventricular zone in dogs have a shorter tumour-specific survival and a higher rate of progression and CNS-metastasis. Despite local tumour control, metastasis must be considered and should prompt further treatment approaches.

Pretreatment MRI in Primary Rectal Cancer as a Predictor for Oncological Outcomes After Surgery for Local Recurrence.

For patients with locally recurrent rectal cancer (LRRC) extensive surgery is often the only curative option and patient selection is crucial. This study aimed to investigate whether magnetic resonance imaging (MRI) characteristics of the primary tumour can predict oncological outcome after surgery for locally recurrent rectal cancer (LRRC). All patients undergoing surgery for LRRC with a curative intent at the Karolinska University Hospital 2003-2013 were included. MRI examinations of the primary tumour were re-evaluated. In total, 54 patients were included. A tumour volume decrease of <70% after preoperative radiotherapy or chemoradiotherapy (C)RT for the primary tumour was correlated with a lower proportion of R0 resection of the LRRC (OR=0.07, 95% CI=0.01-0.84). No association between MRI characteristics of the primary tumour and prognosis after LRRC surgery was found. Long-term outcomes after surgery for LRRC were not significantly associated with MRI characteristics of the index tumour. However, factors associated with increased risk of R1 resection of LRRC were identified.